Global consensus theorem and self-organized criticality: unifying principles for understanding self-organization, swarm intelligence and mechanisms of carcinogenesis.

Gene regulation and systems biology Pub Date : 2013-01-01 Epub Date: 2013-02-20 DOI:10.4137/GRSB.S10885
Simon Rosenfeld
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引用次数: 24

Abstract

Complex biological systems manifest a large variety of emergent phenomena among which prominent roles belong to self-organization and swarm intelligence. Generally, each level in a biological hierarchy possesses its own systemic properties and requires its own way of observation, conceptualization, and modeling. In this work, an attempt is made to outline general guiding principles in exploration of a wide range of seemingly dissimilar phenomena observed in large communities of individuals devoid of any personal intelligence and interacting with each other through simple stimulus-response rules. Mathematically, these guiding principles are well captured by the Global Consensus Theorem (GCT) equally applicable to neural networks and to Lotka-Volterra population dynamics. Universality of the mechanistic principles outlined by GCT allows for a unified approach to such diverse systems as biological networks, communities of social insects, robotic communities, microbial communities, communities of somatic cells, social networks and many other systems. Another cluster of universal laws governing the self-organization in large communities of locally interacting individuals is built around the principle of self-organized criticality (SOC). The GCT and SOC, separately or in combination, provide a conceptual basis for understanding the phenomena of self-organization occurring in large communities without involvement of a supervisory authority, without system-wide informational infrastructure, and without mapping of general plan of action onto cognitive/behavioral faculties of its individual members. Cancer onset and proliferation serves as an important example of application of these conceptual approaches. In this paper, the point of view is put forward that apparently irreconcilable contradictions between two opposing theories of carcinogenesis, that is, the Somatic Mutation Theory and the Tissue Organization Field Theory, may be resolved using the systemic approaches provided by GST and SOC.

全局共识定理和自组织临界性:理解自组织、群体智能和致癌机制的统一原则。
复杂的生物系统表现出各种各样的涌现现象,其中自组织和群体智能发挥着突出的作用。一般来说,生物层次中的每一个层次都有自己的系统属性,需要自己的观察、概念化和建模方式。在这项工作中,试图概述一般指导原则,以探索在缺乏任何个人智力的个体的大型社区中观察到的各种看似不同的现象,并通过简单的刺激-反应规则相互作用。数学上,这些指导原则被全局共识定理(GCT)很好地捕获,同样适用于神经网络和Lotka-Volterra种群动态。GCT概述的机制原理的普遍性允许对生物网络、群居昆虫群落、机器人群落、微生物群落、体细胞群落、社会网络和许多其他系统等不同系统采用统一的方法。在本地相互作用的个人组成的大型社区中,管理自组织的另一组普遍规律是围绕自组织临界性(SOC)原则建立的。GCT和SOC,单独或结合,为理解在没有监管机构参与、没有系统范围的信息基础设施、没有将总体行动计划映射到个体成员的认知/行为能力的情况下,大型社区中发生的自组织现象提供了概念基础。癌症的发生和增殖是应用这些概念方法的一个重要例子。本文提出的观点是,两种截然对立的致癌理论,即体细胞突变理论和组织组织场理论之间明显不可调和的矛盾,可以用GST和SOC提供的系统方法来解决。
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